40 citations · 49 across the 3 of their papers we have counts for
4 papers
Robust and integrative Bayesian neural networks for likelihood-free parameter inference
Fredrik Wrede, Robin Eriksson, Richard Jiang +4
State-of-the-art neural network-based methods for learning summary statistics have delivered promising results for simulation-based likelihood-free parameter inference. Existing ap…
Initialization of a Disease Transmission Model
Håkan Runvik, Alexander Medvedev, Robin Eriksson +1
Approaches to the calculation of the full state vector of a larger epidemiological model for the spread of COVID-19 in Sweden at the initial time instant from available data and wi…
Bayesian epidemiological modeling over high-resolution network data
Stefan Engblom, Robin Eriksson, Stefan Widgren
Mathematical epidemiological models have a broad use, including both qualitative and quantitative applications. With the increasing availability of data, large-scale quantitative d…
Privacy Odometers and Filters: Pay-as-you-Go Composition
Ryan Rogers, Aaron Roth, Jonathan Ullman +1
In this paper we initiate the study of adaptive composition in differential privacy when the length of the composition, and the privacy parameters themselves can be chosen adaptive…